A informática como uma ferramenta de apoio a inclusão do deficiente visual

An inclusive environment has its foundations in the belief that all people are entitled to participate, to live as normal a life as possible, without discrimination, especially in education. This is to ensure equal opportunities. For individuals with special needs, the use of computers and digital materials is not an alternative, but one of the only forms of access to information. For the visually impaired, they start from the beginning to enter the university, through the selection processes, not always accessible. For those who can, other difficulties arise, undermining the initial enthusiasm and generating a large rate of dropouts. In most cases, these students will depend on the goodwill of colleagues and volunteers for the reading of texts in the basic literature of the disciplines studied. The high cost of technology assisted allied to a lack of resources and knowledge of curricular adaptations, prevents many teachers help these students in an appropriate manner. This thesis seeks to contribute to the inclusion of the visually impaired student pointing alternatives that can help in caring education. The research was conducted specifically for the doctorate during the period 2001 to 2006, the cities of Natal, Salvador and Curitiba, and is based mainly on the methodology of action research. The objective was the construction of Virtual Teaching Support Center , structured in a Web portal that can serve as a resource to help support teachers, staff and other users concerned with the process of inclusion of people with needs special education, with the goal of assimilation of educational opportunities, with the support of resources and methods. The inclusion is for everyone because we are all different

Seleção de features guiada por atenção visual em imagens com fóvea

Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom-up or top-down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top-down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as Speeded Up Robust Features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics